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Community Texts
Jun 27, 2023
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Coronavirus 2019 (COVID-19), as a common infectious disease, is spreading rapidly and uncontrollably worldwide. Therefore, early detection of mortality considering the symptoms that appear in patients with Coronavirus is important. The main aim of this study is investigating the effect of data preprocessing methods on the efficiency of data mining approaches. In this study, we propose a hybrid method based on the Covid-19 dataset to predict the mortality of 1255 patients with coronavirus that...
Topics: COVID-19, Artificial Intelligence, Data Mining, Feature Selection, KNIME Tool
Community Texts
Jun 27, 2023
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Few-shot learning assumes that we have a very small dataset for each task and trains a model on the set of tasks. For real-world problems, however, the amount of available data is substantially much more; we call this a medium-shot setting, where the dataset often has several hundreds of data. Despite their high accuracy, deep neural networks have a drawback as they are black-box. Learning interpretable models has become more important over time. This study aims to obtain sample-based...
Topics: Bayesian Meta-Learning, Medium-shot Learning, Sample-based Interpretability, Sparse Kernel,...
Community Texts
Jun 27, 2023
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For more comprehensive security of a computer network as well as the use of firewall and anti-virus security equipment, intrusion detection systems (IDSs) are needed to detect the malicious activity of intruders. Therefore, the introduction of a high-precision intrusion detection system is critical for the network. Generally, the general framework of the proposed intrusion detection models is the use of text classification, and today deep neural networks (DNNs) are one of the top classifiers. A...
Topics: Intrusion detection, Software-defined network, Deep learning, Network security
Community Texts
Jun 25, 2023
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Social networks have become a central part of our lives these days and have real effects on the world's events. However, social networks greatly boost spreading misinformation and rumors that are becoming more and more dangerous each day. As fighting rumors first requires detecting them, several researchers tried to propose novel approaches for automatic early detection of rumors. However, most of them rely on handcrafted content features which makes them prone to deception and threats the...
Topics: Deception, Deep learning, Social network, Twitter
Community Texts
Jun 25, 2023
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Representation learning on a knowledge graph aims to capture patterns in the knowledge graph as low-dimensional dense distributed representation vectors in the continuous semantic space, which is a powerful technique for predicting missing links in knowledge bases. The problem of knowledge base completion can be viewed as predicting new triples based on the existing ones. One of the prominent approaches in knowledge base completion is the embedding model. Currently, the majority of existing...
Topics: Knowledge Graphs, Link Prediction, Positive Samples, Embedding Neural Network, Graph mining
Community Texts
Jun 25, 2023
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With the aid of intelligent system approaches, the present study aimed at extracting and investigating effective features for detecting Attention-Deficit/Hyperactivity Disorder (ADHD) in children. With this end in view, 103 children, aged from 6 to 10, were recruited for this study, among which 49 cases were assigned to the treatment group (ADHD children) and the remaining 54 cases to the control group (healthy children). The disorder diagnosis was performed using the well-known, relevant...
Topics: Attention Deficit Hyperactivity Disorder (ADHD), EEG/Evoked Potentials, Feature Extraction
Community Texts
Jun 25, 2023
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Todays, although social networks are used for extensive information sharing, spreading rumors has also been accelerated and become a serious problem. Rumor control can be accomplished through either hard or soft control strategies. The former uses depriving actions like blocking rumor spreaders, while the latter tries to persuade people personally avoiding rumor propagation by increasing their knowledge and awareness. Although there are some proposals for rumor control in social networks,...
Topics: Evolutionary Game Theory, Rumor spreading, Rumor control, Social network
Community Texts
Jun 25, 2023
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Neural Architecture Search (NAS), which automatically designs a neural architecture for a specific task, has attracted much attention in recent years. Properly defining the search space is a key step in the success of NAS approaches, which allows us to reduce the required time for evaluation. Thus, late strategies for searching a NAS space is to leverage supervised learning models for ranking the potential neural models, i.e., surrogate predictive models. The predictive model takes the...
Topics: Neural Architecture Search, Search Space Pruning, Network Architecture, Representation Learning
Community Texts
Jun 25, 2023
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The problem of influence maximization is selecting the most influential individuals in a social network. With the popularity of social network sites and the development of viral marketing, the importance of the problem has increased. The influence maximization problem is NP-hard, and therefore, there will not exist any polynomial-time algorithm to solve the problem unless P = NP. Many heuristics are proposed for finding a nearly good solution in a shorter time. This study proposes two heuristic...
Topics: Degree centrality, Heuristic algorithm, Independent cascade model, Influence maximization
Community Texts
Jun 24, 2023
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The problem of influence maximization is selecting the most influential individuals in a social network. With the popularity of social network sites and the development of viral marketing, the importance of the problem has increased. The influence maximization problem is NP-hard, and therefore, there will not exist any polynomial-time algorithm to solve the problem unless P = NP. Many heuristics are proposed for finding a nearly good solution in a shorter time. This study proposes two heuristic...
Topics: Degree centrality, Heuristic algorithm, Independent cascade model, Influence maximization
Community Texts
Jun 24, 2023
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A complex system is a system that has many components that are interdependent and appear as a whole and exhibit organized behavior. Community structure detection is an optimization problem in complex networks that involves searching for communities belonging to a network that shares nodes of a similar community with standard features. In this paper, we use a multi-agent memetic algorithm to detect the structure of the community in complex networks by optimizing the amount of modularity and...
Topics: Complex systems, Multi-agent systems, Memetic algorithm, Community detection
Community Texts
Jun 24, 2023
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In cloud computing, task scheduling is one of the most important issues that need to be considered for enhancing system performance and user satisfaction. Although there are many task scheduling strategies, available algorithms mainly focus on reducing the execution time while ignoring the profits of service providers. In order to improve provider profitability as well as meet the user requirements, tasks should be executed with minimal cost and without violating Quality of Service (QoS)...
Topics: Cloud, Task scheduling, Cost, Energy consumption, Makespan
Community Texts
Jun 24, 2023
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Nowadays, prediction and decision making are two inseparable principles in the management and two distinct roles of managers. The organizations spend a large part of their budgets on predictions from past data. They will lose their money if they are neglected. On the other hand, decision-making is the most critical step in problem-solving. Moreover, it is considered the main task of a manager as a problem solver. Making decision becomes more complicated when we are faced with multi-criteria...
Topics: Analytical hierarchy process, deep Learning, decision making, regression
Community Texts
Jun 24, 2023
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This study investigates the application of the Black Hole algorithm (BH) for solving 0–1 knapsack problems. Knapsack problem is a classic and famous problem for testing and analyzing the behavior of optimization and meta-heuristic algorithms. There is no single algorithm which is suitable for all types of the knapsack problem. So it is an open research area to solve knapsack problem using novel optimization algorithms efficiently. BH algorithm is one of the most recent nature-inspired...
Topics: Knapsack Problems, Black Hole Algorithm, Optimization
Community Texts
Jun 24, 2023
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Due to the increasing deployment of vehicles in human societies and the necessity for smart traffic control, anomaly detection is among the various tasks widely employed in traffic monitoring. As the issue of urban traffic and their relative smart monitoring systems have gained popularity among researchers in recent years, there exist several studies in this regard. In most of these studies, classification is performed based on the behavior of drivers, where a set of default trajectories are...
Topics: Neural-Fuzzy Inference System, Autoencoder Neural Network, Deep Neural Network, Trajectory Anomaly...
Community Texts
Jun 20, 2023
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Full adder is one of the essential circuits among the various processing elements used in VLSI and other technologies circuits, because they are mainly employed in other arithmetic circuits, such as multi-digit adders, subtractors, and multipliers. This paper proposes two efficient ternary full adders based on Carbon Nanotube Field-Effect Transistor (CNFET) technology. Using the adjustable nanotube diameter in CNFETs, these adders utilize arbitrary threshold voltages so that arithmetic...
Topics: Nanotechnology, Ternary Logic, Multi-Value Logic, Ternary Adder, CNFET
Community Texts
Jun 20, 2023
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Software testing is one of the most important activities for ensuring quality of software products. It is a complex and knowledge-intensive activity which can be improved by reusing tester knowledge. Generally, testing web applications involve writing manual test scripts, which is a tedious and labor-intensive process. Manually written test scripts are valuable assets encapsulating the knowledge of the testers. Reusing these scripts to automatically generate new test scripts can improve the...
Topics: Automated testing, semantic web, Test adaptation, Test generation, Test ontology
Community Texts
Jun 20, 2023
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Automatic text classification, which is defined as the process of automatically classifying texts into predefined categories, has many applications in our everyday life and it has recently gained much attention due to the in-creased number of text documents available in electronic form. Classifying News articles is one of the applications of text classification. Automatic classification is a subset of machine learning techniques in which a classifier is built by learning from some...
Topics: Automatic Persian text classification, K-Nearest Neighbor, Naïve Bayes, News text classification,...
Community Texts
Jun 19, 2023
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Probabilistic model checking is a formal method for verification of the quantitative and qualitative properties of computer systems with stochastic behaviors. Markov Decision Processes (MDPs) are well-known formalisms for modeling this class of systems. Bounded reachability probabilities are an important class of properties that are computed in probabilistic model checking. Iterative numerical computations are used for this class of properties. A significant draw-back of the standard iterative...
Topics: probabilistic model checking, Iterative numerical methods, Bounded Reachability probabilities,...
Community Texts
Jun 19, 2023
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Metabolic Syndrome (MS) is the collection of risk factors for coronary artery disease (CAD). It is responsible for cardiovascular disease (CVD), type 2 diabetes, cancer, renal and mental diseases with the transition from childhood to adulthood. The MS is increasing in recent decades in different societies, especially in Iran. This study was conducted to determine the predictive factors of MS in children and adolescents in Birjand (Capital of South Khorasan Province, Iran) using a data mining...
Topics: Index Terms, Metabolic Syndrome, Data Mining, Decision Tree, School-Age Population
Community Texts
Jun 19, 2023
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One of the most challenging aspects of developing information systems is the processing and management of large volumes of information. One way to overcome this problem is to implement efficient data indexing and classification systems. As large volumes of generated data comprise of non-structured textual data, developing text processing, management and indexing frameworks can play an important role in providing users with accurate information according to their preferences. In this paper, a...
Topics: Ontology, Knowledge Base, Semantic Indexing, Knowledge-based Information System, Semantic Network...
Community Texts
Jun 19, 2023
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This paper proposes new algorithms to improve Reinforcement Learning (RL) and Deep Q-Network (DQN) methods for path planning considering uncertainty in the perception of environment. The study aimed to formulate and solve the path planning optimization problem by optimizing the path, avoiding obstacles, and minimizing the related uncertainty. In this regard, a reward function is constructed based on the weighted features of the environment images. In this study, Deep Learning (DL) is used for...
Topics: Reinforcement Learning, Deep Learning, Q-learning, Path Planning, Deep Q-Network (DQN)
Community Texts
Jun 19, 2023
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The goal of this research is to create a reference data model for educational and research institutes of Iranian Ministry of Sciences, Research, and Technology. After investigating existing technologies and considering the problem context, ontology was chosen as the data model format. In order to create the target ontology, an ontology construction methodology was designed and implemented. This methodology is created using design science research method and contains an architecture, a detailed...
Topics: Ontology Development, Higher Education Ontology, Ontology Learning
Community Texts
Jun 19, 2023
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In the recent years, the Internet of things (IoT) applications have affected many aspects of human life due to the continuous innovation in hardware, software, and communication technologies along with the growth of the connected devices. The enormous amounts of data generated by these devices must be stored and then processed for analysis and decision-making. One promising solution for this purpose is cloud computing. However, offloading tasks to the cloud imposes costs that must be reduced by...
Topics: Index terms, Cloud computing, the Internet of things, Spot instances, Task offloading
Community Texts
Jun 19, 2023
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Software-Defined Networking (SDN) is a viable approach for management of large and extensive networks with flexible quality of service requirements and huge data traffic. Due to the central role of SDN controllers in traffic engineering and performance of software-defined networks on one hand, and diversity of available SDN controllers on the other hand, an evaluation framework is required to study and compare the architectural choices and performance of distributed and centralized SDN...
Topics: Software-Defined Networking (SDN), OpenFlow Controllers, Performance Evaluation, Quality of Service
Community Texts
Jun 19, 2023
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With the advent of the internet, along with email, and social networking, there are some new issues that have caused vulnerability of users against attackers. Internet users face a lot of undesirable emails and their data privacy and security is in danger. Spammers are often sent to users by intruders and sales markets, and most of the time they target spam, harassment, and abuse of user data. With increasing attacks on computer networks, attempts to rebuild computer networks and detect spam...
Topics: Email spam detection, Feature selection, Particle swarm optimization, Fruit fly optimization
Community Texts
Jun 19, 2023
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Given the financial crises in the world, one of the most important issues of banking industry is the assessment of customers' credit to distinguish bad credit customers from good credit customers. The problem of customer credit risk assessment is a binary classification problem, which suffers from the lack of data and sophisticated features as main challenges. In this paper, an adaptive neuro-fuzzy inference system is exploited to tackle the customer credit risk assessment problem regarding the...
Topics: Banking, Customer credit risk, Risk Assessment, Fuzzy system
Community Texts
Jun 19, 2023
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The increment of computer technology usage and rapid development of the Internet and electronic business lead to an increase in financial transactions. With the increase of these banking activities, fraudsters also use different methods to boost their fraudulent activities. One of the ways to cope their damages is fraud detection. Although, in this field, some methods have been proposed, there are essential challenges on the way. For example, it is necessary to propose methods that detect fraud...
Topics: Fraud, Fraud detection, Semi-supervised learning, Evolutionary algorithm, Feature extraction
Community Texts
Jun 19, 2023
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Previous studies show that the incorporation of spatial features in the classification process of hyperspectral images (HSI) improves classification accuracy. Although different spatial-spectral methods are proposed in the literature for the classification of the HSI, they almost have a slow, complex, and parameter-dependent structure. This paper proposes, a simple, fast and efficient two-stage spatial-spectral method for the classification of the HSI based on extended morphological profiles...
Topics: Extended Morphological Profiles, Guided Filter, Support vector machine, Principal Components...
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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In a large-scale wireless sensor network (WSN), the nodes are usually randomly spread. In such a network, more active nodes consume more energy and shorten the network lifetime. An appropriate approach is nodes management, mainly turning off or deactivating some redundant nodes during some periods of time. The redundant nodes are those that deactivating them does not affect the overall objective operation of the network such as full connectivity and coverage. In this paper two methods for...
Topics: wireless sensor network, large-scale wireless sensor network, node management, network connectivity
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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The Operating System (OS) is a major part of embedded software systems and its robustness has considerable influence on the robustness of the entire system. Thus, its robustness testing is critical for assessing the dependability of the system. In this paper, a state-aware approach is proposed to evaluate the robustness of components of embedded real-time OSs in the presence of different types of faulty inputs. This approach leads to identifying critical OS states, their criticality level, and...
Topics: Robustness testing, Robustness level assessment, Safety-critical systems, Fault injection
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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Nowadays, routing and the improvement of reliability along with the load balancing and congestion control are the most important and challenging concepts in ad-hoc networks. However, there are some constraints in the bandwidth and the communication range due to the different utility of routing in the Mobile Ad Hoc Network (MANET). These restrictions, in addition to the dynamic network topology, are causing more complexity of routing and data transmission. These problems make the use of...
Topics: MANET, AOMDV, Reactive Routing, Congestion control
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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Since the invention of electricity, global power grids have been at the forefront of technological advances. The antiquated infrastructure of power system which provides power to the city's homes, factories and businesses are replaced with a new power distribution system. This new infrastructure of power distribution includes the collection of digital systems called the smart grid. In the smart grid, one of the main components is the distribution system, and the consumption reports are...
Topics: session key, authentication, key agreement, smart grid, security
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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In this article, one of the most important methods of steganography on VoIP called echo hiding is improved. This method has advantages in maintaining the statistical and perceptual characteristics of audio signals as well as security against the sensitivity of human audio system (HAS). However, it has lots of errors in detecting coded and hidden messages, which is detectable using existing steganalysis methods. The percentage of extracting messages in these improved methods of echo hiding is...
Topics: steganography, echo hiding, spread spectrum, safety, cepstral coefficients, self-symmetric
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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A vision-based intelligent traffic control system is a robust framework that controls the traffic flow in real-time by estimating the traffic density near traffic lights. In this paper, a traffic light control system based on fuzzy Q-learning is proposed according to the vehicle density and the pedestrian number estimated from the visual information. The aim of proposed approach is to minimize the pedestrian and the car waiting time and maximize throughput for an isolated 4-way traffic...
Topics: Intelligent traffic control system, traffic density, fuzzy logic, traffic light control
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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The goal of many tasks in the realm of sequence processing is to map a sequence of input data to a sequence of output labels. Long short-term memory (LSTM), a type of recurrent neural network (RNN), equipped with connectionist temporal classification (CTC) has been proved to be one of the most suitable tools for such tasks. With the aid of CTC, the existence of per-frame labeled sequences are no longer necessary and it suffices to only knowing the sequence of labels. However, in CTC, only a...
Topics: connectionist temporal classification, handwriting recognition, recurrent neural networks,...
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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This research with attention to the establishment of trust in WSNs and with the goal of increment in energy supply and growth in malicious node detection accuracy by using of improved sliding window, is saving energy by using computation of the previous periods. Also, this research calculates the trust in aspect of transferring information, based on subjective logic model and incremented the detection rate of malicious node by proposing two algorithms for identifying these nodes. Then, this...
Topics: trust, wireless sensor network, subjective logic model, sliding window
Miscellaneous Contributed Journals and Academic Newsletters
Jun 13, 2023
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This study proposes a novel routing algorithm using Q-learning. Q-learning is a machine learning (artificial intelligence) algorithm using the reinforcement learning policy which can be used to solve problems for which there are different ways to reach their goal. The proposed algorithm, the Modified Q-learning routing algorithm (MQRA), has eliminated the episodes of Q-learning required to gradually learn in different stages and this has made it a rapid routing algorithm. MQRA can be used in...
Topics: routing algorithm, mobile ad-hoc networks, FSR protocol, reinforcement learning, Routing in MANETs
Miscellaneous Contributed Journals and Academic Newsletters
Jun 12, 2023
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This study proposes a novel routing algorithm using Q-learning. Q-learning is a machine learning (artificial intelligence) algorithm using the reinforcement learning policy which can be used to solve problems for which there are different ways to reach their goal. The proposed algorithm, the Modified Q-learning routing algorithm (MQRA), has eliminated the episodes of Q-learning required to gradually learn in different stages and this has made it a rapid routing algorithm. MQRA can be used in...
Topics: routing algorithm, mobile ad-hoc networks, fsr protocol, reinforcement learning, routing in MANETs
Miscellaneous Contributed Journals and Academic Newsletters
Jun 12, 2023
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Target tracking is estimating the state of moving targets using noisy measurements obtained at a single observation point or node. Particle filters or sequential Monte Carlo methods use a set of weighted state samples, called particles, to approximate the posterior probability distribution in a Bayesian setup. During the past few years, Particle Filters have become very popular because of their ability to process observations represented by nonlinear state-space models where the noise of the...
Topics: distributed particle filter, support vector machines, target tracking, wireless sensor networks
Miscellaneous Contributed Journals and Academic Newsletters
Jun 12, 2023
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placement of virtual sensors in servers of cloud environment is one of the most important issues in resource management of sensor-cloud networks. Virtual sensors allocate resources of cloud servers to themselves, run different applications and use equivalent physical sensors. Selecting an appropriate method for placement of virtual sensors on cloud servers has a significant impact on resource management and energy consumption. Also, because of the real-time requirements of sensor-cloud...
Topics: sensor-cloud networks, virtual sensors, resource management, migratio, energy Consumptionn, traffic
Miscellaneous Contributed Journals and Academic Newsletters
Jun 12, 2023
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β-sheet topology prediction is a major unresolved problem in modern computational biology. It is a challenging intermediate step toward the protein tertiary structure prediction. Different methods have been provided to deal with the problem of determining the β-sheet topology. Here, ab-initio probability-based methods called "BetaProbe1" and "BetaProbe2" are utilized to specify the β-sheet topology. In these methods, the stability and the frequency of β-strand pairwise...
Topics: β-sheet topology prediction, integer programming, dynamic programming, pairwise alignment
Miscellaneous Contributed Journals and Academic Newsletters
Jun 12, 2023
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in real-time task scheduling on multiprocessor systems, partitioning approach has received the attention of many researchers because of its higher least upper bound utilization of safe systems. Semi-partitioning allows some tasks to be split into subtasks and each subtask to be assigned to a different processor. Though task splitting improves the performance of systems, by counting each subtask as a separate task, it increases the effective number of tasks to be scheduled, which in turn, raises...
Topics: rate-monotonic least splitting, semi-partitioning, hard real-time, multiprocessor scheduling
Miscellaneous Contributed Journals and Academic Newsletters
May 29, 2023
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nowadays, cloud computing and other distributed computing systems have been developed to support various types of workflows in applications. Due to the restrictions onthe use ofone cloud provider, the concept of multiple clouds as been proposed.Inmultipleclouds, schedulingworkflowswithlarge amounts ofdata is a well-knownNP-Hard problem. The existing scheduling algorithms have not paid attention to the data dependency issues and their importance in scheduling criteria such as time and cost. In...
Topics: cloud computing, multi-cloud, workflow scheduling, data dependency communication
Various applications with different requirments are rapidly developed in the smart grid. The need to provide Quality of Service (QoS) for such a communication network is inevitable. However, recently a protocol called RPL (Routing Protocol for Low Power and Lossy Network) has been standardized and is known as the main solution for last mile communication network of smart grid. In this paper, by studying the existing methods and identifying the shortcomings, we propose a customized version of...
Topics: RPL, DODAG, QoS
owadays, cloud computing and other distributed computing systems have been developed to support various types of workflows in applications. Due to the restrictions onthe use ofone cloud provider, the concept of multiple clouds as been proposed.Inmultipleclouds, schedulingworkflowswithlarge amounts ofdata is a well-knownNP-Hard problem. The existing scheduling algorithms have not paid attention to the data dependency issues and their importance in scheduling criteria such as time and cost. In...
Topics: cloud computing, multi-cloud, workflow scheduling, data dependency, communication
In the emerging field of the Internet of Things (IoT), Wireless Sensor Networks (WSNs) play a key role in sensing and collecting data from the surrounding environment. In the deployment of large-scale monitoring systems in remote areas, when there is not a permanent connection with the Internet, WSNs are called upon for replication and distributed storage techniques that increase the amount of data storage within the WSN and reduce the probability of data loss. Unlike conventional network data...
Topics: the internet of things, distributed storage, energy efficient